Agentic Software Engineer

Location: Poland (remote) Work Schedule: Full-time Contract Type: pure B2B (JDG) A Market Intelligence Suite is being developed by our client in order to bring together and provide a visual representation of large amounts of market data, key performance indicators, and analytical insights from various markets, giving business users a full overview of market performance and trends. The product has already reached a workable stage and comprises a wide variety of dashboards, market views, KPIs and analytical features. The first version of the solution was developed by a small group of subject matter experts using AI-assisted or vibe-coding methods, not with the help of a traditional software development team. As the product keeps on growing and the number of feature requests rises, we are seeking an Agentic Software Engineer who will bring strong software engineering skills and at the same time keep up the speed, experimentation and AI-first approach that made it possible for the product to develop so rapidly. The engineer will work directly with domain experts who have a deep knowledge of the business ecosystem and will assist in turning their ideas and requirements into actual product capabilities. The position will involve carrying out rapid feature development with the aid of AI while at the same time following software engineering best practices. As well as developing new features, the engineer will assist in strengthening the technical basis of the product by introducing the relevant practices in the areas of architecture, authentication and authorization, security, testing, maintainability, observability and reliable delivery. It doesn't involve the kind of development typically expected. What we're after is someone who actually takes pleasure in experimenting with AI, who keeps up to date with new models and development tools, comes up with their own ideas, and always seeks out improved methods for building software using AI. Requirements: Solid hands-on experience in software engineering and a record of developing modern web applications.Gaining practical experience by using AI coding agents and LLM-based development tools to develop actual software.A true passion for AI, agentic engineering and AI-assisted software development.Experience in using tools such as Claude Code, Cursor, Codex, GitHub Copilot or other similar AI coding environments.The ability to convert a business problem, a feature request, or a vaguely defined idea into a working product solution on one's own.Have experience working with applications that involve large amounts of data, as well as with dashboards, analytics, and data visualization.A solid understanding of the architecture of modern web applications and of the principles of software engineering.An understanding of authentication, authorization, access control, and application security in a practical way.Gain experience in integrating applications with APIs, external services, and various data sources.The ability to understand, check, debug, restructure, and improve code that has been generated by AI.Having a good understanding of testing, maintainability, logging, monitoring and the reliable delivery of software.The ability to combine rapid experimentation and delivery with sustainable engineering practices.A strong sense of ownership and the capacity to work on one's own without the need for detailed technical specifications.A strong product mindset, with a focus on solving business problems rather than just carrying out technical tasks.A proactive attitude means having the ability to question current methods, propose improvements, and introduce new product and technical ideas.A high level of curiosity together with a constant desire to experiment with new AI models, coding agents, tools, and workflows.Having strong communication and collaboration skills when working directly with business or domain experts.Experience gained through using JavaScript/TypeScript, Node.js, Python or other modern development technologies is relevant; yet the use of any particular technology stack is not a major factor in the selection process.Will be a plus Have experience developing market intelligence, business intelligence, analytics, or data-intensive products.Have implemented enterprise authentication, single sign-on, and role-based access control (RBAC)Knowledge of cloud platforms and contemporary methods of deploying applications.Have experience in developing analytics or conversational interfaces that are powered by AIHave experience in designing reusable agentic workflows or automation for software developmentTry out a variety of AI models and coding agents and then choose the appropriate tools for each particular taskExamples of personal AI projects, prototypes, entries in hackathons, or internal products which show practical experimentation with AI-first development.There is a keen interest in new AI engineering tools and methods. Responsibilities: Create and continuously improve new features and capabilities for the existing Market Intelligence Suite.Deal directly with specialists in the field to get a clear understanding of business requirements and then convert these into actual product features.Spread the dashboards, market views, key performance indicators, and analytical capabilities over a number of markets.Take responsibility for the development of a feature from the very first idea and the creation of a rapid prototype right through to its implementation and validation.Make extensive use of AI coding agents at all stages of the software development lifecycle, including during implementation, debugging, testing, refactoring and documentation.Make sure that the current AI-generated codebase is understood, its issues are acknowledged, and it is constantly improved.As the product develops, incorporate suitable software engineering best practices.Implement the authentication, authorization and access-control mechanisms and then improve them.Improve the application's architecture, security, maintainability, testing, and reliability.As the product's capabilities develop, incorporate further data sources, APIs, and external services.Improve logging, monitoring, observability, and troubleshooting capabilities.Quickly prototype new ideas, check them together with experts in the field, and make improvements according to the feedback.Keep on assessing new AI models, coding agents and development tools and incorporate methods that can enhance both the speed and quality of development.Identify actively the opportunities for new product features, automation and more efficient methods of solving business problems.Where suitable, question the current methods and suggest improved technical or product solutions.Assist the broader team in constantly improving its AI-first/agentic engineering practices.